Let E be the event of an even number of successes.
$u_n$:Probability of E occurring at the nth trial not necessarily for the first time
$f_n$:Probability of E occurring at the nth trial for the first time
Let U(x) and F(x) be the corresponding probability generating functions and from that we have the equation $$U(x)=1/(1-F(x))$$ I first wrote a recurrence formula $u_n=p(1-u_{n-1})+qu_{n-1}$
By solving this I got $$U(x)=px/[(1-x)(1-(q-p)x)]$$
Intuitively I feel $F(x)$ should be $p^2x^2/(1-qx)^2$ since this event can be taken as the sum of two geometric random variables. However this is not what I get from the $U(x)$ that I have computed. Did I do something wrong? Any assistance will be very helpful to me. Thanks alot
EDIT: In an answer I saw $u_n$ taken as $[1-(q-p)^{n-1}]p$ which gives results in the $F(x)$ of sum of two random geometric variables but I do not know how this $u_n$ was constructed
Here's a way to do by using a Markov chain:
\begin{align*} A &= \begin{pmatrix} q & p & 0 \\ 0 & q & p \\ q & p & 0 \end{pmatrix} \end{align*}
Answer will be the third column of the first row in $A^n$, and the generating function for all entries can be obtained directly from the matrix by computing \begin{align*} \left(I-x\, A\right)^{-1} \end{align*}
Thus, the gf for the required entry is: \begin{align*} G(x) &= -\frac{p^{2} x^{2}}{{\left(p^{2} - q^{2}\right)} x^{2} + 2 \, q x - 1} \end{align*} and by partial fractions, \begin{align*} G(x) &= \frac{p^2}{q-p}+\frac{p}{2}\left(\frac{1}{1-x}-\frac{1}{\left(q-p\right)\left(1-(q-p)\, x\right)}\right) \end{align*} Hence, the solution for $u_n$ is given by $[x^n]$, which is \begin{align*} u_n &= \frac{p}{2}\left(1-(q-p)^{n-1}\right) \end{align*}
Update
We can obtain the recurrence using the markov chain as:
\begin{align*} u_n &= p\, v_{n-1} \\ v_n &= p\, \left(u_{n-1}+w_{n-1}\right)+q\, v_{n-1} \\ w_n &= q\, \left(u_{n-1}+w_{n-1}\right) \\ u_1 &= 0 \\ v_1 &= p \\ w_1 &= q \\ u_2 &= p^2 \\ v_2 &= 2pq \\ w_2 &= q^2 \\ \end{align*} $u_n$ is the required answer.
$w_n$ gives the probability of even number of successes, but not exactly at the $n^{th}$ trial.
$v_n$ is for the odd number of successes.